Wind power is considered one of the cleanest, most environmentally friendly energy sources presently available, and wind turbines have gained increased attention in this regard. A modern wind turbine typically includes a tower, generator, gearbox, nacelle, and one or more rotor blades. The rotor blades capture kinetic energy of wind using known airfoil principles. For example, rotor blades typically have the cross-sectional profile of an airfoil such that, during operation, air flows over the blade producing a pressure difference between the sides. Consequently, a lift force, which is directed from a pressure side towards a suction side, acts on the blade. The lift force generates torque on the main rotor shaft, which is geared to a generator for producing electricity.
A plurality of wind turbines are commonly used in conjunction with one another to generate electricity and are commonly referred to as a “wind farm.” Wind turbines on a wind farm typically include their own meteorological monitors that perform, for example, temperature, wind speed, wind direction, barometric pressure, and/or air density measurements. In addition, a separate meteorological mast or tower (“met mast”) having higher quality meteorological instruments that can provide more accurate measurements at one point in the farm is commonly provided. The correlation of meteorological data with power output allows the empirical determination of a “power curve” for the individual wind turbines.
Typically, in a wind farm, each wind turbine attempts to maximize its own power output while maintaining its fatigue loads within desirable limits. To this end, each turbine includes a control module, which attempts to maximize power output of the turbine in the face of varying wind and grid conditions, while satisfying constraints like sub-system ratings and component loads. Based on the determined maximum power output, the control module controls the operation of various turbine components, such as the generator/power converter, the pitch system, the brakes, and the yaw mechanism to reach the maximum power efficiency.
Often, while maximizing the power output of a single wind turbine, neighboring turbines may be negatively impacted. For example, downwind turbines may experience large wake effects caused by an upwind turbine. Wake effects include reduction in wind speed and increased wind turbulence downwind from a wind turbine typically caused by the conventional operation of upwind turbines (for maximum power output). Because of these wake effects, downwind turbines receive wind at a lower speed, drastically affecting their power output (as power output is proportional to wind speed). Moreover, wind turbulence negatively affects the fatigue loads placed on the downwind turbines, and thereby affects their life (as life is proportional to fatigue loads). Consequently, maximum efficiency of a few wind turbines may lead to sub-optimal power output, performance, or longevity of other wind turbines in the wind farm. Thus, modern control technologies attempt to optimize the wind farm power output rather than the power outputs of each individual wind turbine.
In addition, there are many products, features, and/or upgrades available for wind turbines and/or wind farms so as to increase power output, e.g. annual energy production (AEP), of the wind farm. As new and improved upgrades become available, it is advantageous to quickly and efficiently determine whether a specific wind turbine of the wind farm can receive the upgrade without, for example, exceeding operating load limits.
For example, some wind farms employ a plurality of load sensors for each wind turbine. Each sensor has an associated margin that indicates whether a particular wind turbine component is operating safely. A farm controller receives data from the load sensors and performs a load analysis for each wind turbine within the wind farm. If the wind turbine passes the load analysis (i.e. each sensor is operating within its margin), then the turbine may receive an upgrade. Such control technologies, however, are very time-consuming, as the load analysis has to be performed for each wind turbine in the wind farm.
Additional wind farm controllers determine whether individual wind turbines can receive an upgrade by approximating loads for each wind turbine using pre-existing wind turbine data, e.g. data stored in one or more look-up tables. Based on the approximation, the farm controller can perform a loads analysis for the most-loaded turbines, rather than all of the wind turbines, so as to reduce the amount of time required to perform the analysis. Such a loads analysis, however, may not be as accurate as performing the loads analysis on each turbine using one more load sensors as described above. In addition, using the most-loaded turbine may be too conservative of an estimate, thereby sacrificing potential gains.
Accordingly, there is a need for improved systems and methods for optimizing wind farm performance that addresses the aforementioned issues.